Comprehensive models for evaluating rockmass stability based on statistical comparisons of multiple classifiers

Mathematical Problems in Engineering

Volumn 2013, Issue , 2013, Pages

  Dong, Longjun ^a   Li, Xibing ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION PERFORMANCE; GEOLOGICAL ENVIRONMENT; LOGISTIC REGRESSIONS; MULTIPLE INTELLIGENCES; RANDOM FOREST MODELING; RECEIVER OPERATING CHARACTERISTIC CURVES; STATISTICAL COMPARISONS; SUPPORT VECTOR MACHINE MODELS;

DECISION TREES; ROCKS; SUPPORT VECTOR MACHINES;

SLOPE STABILITY;

EID: 84884898069     PISSN: 1024123X     EISSN: 15635147     Source Type: Journal    
DOI: 10.1155/2013/395096     Document Type: Article

References (45)

1. Sakellariou M. G., Ferentinou M. D., A study of slope stability prediction using neural networks. Geotechnical and Geological Engineering 2005 23 4 419 445 2-s2.0-23844474449 10.1007/s10706-004-8680-5 (Pubitemid 41149150)
2. Dong L.-J., Li X.-B., Interval non-probabilistic reliability method for surrounding jointed rock mass stability of underground caverns. Chinese Journal of Geotechnical Engineering 2011 33 7 1007 1013 2-s2.0-80051572950
3. Dong L.-J., Li X.-B., Interval parameters and credibility of representative values of tensile and compression strength tests on rock. Chinese Journal of Geotechnical Engineering 2010 32 12 1969 1974 2-s2.0-78651421872
4. Dong L., Li X., Zhou Z., Nonlinear model-based support vector machine for predicting rock mechanical behaviors. Advanced Science Letters 2012 5 806 810
5. Rajesh Kumar B., Vardhan H., Govindaraj M., Vijay G., Regression analysis and ANN models to predict rock properties from sound levels produced during drilling. International Journal of Rock Mechanics and Mining Sciences 2013 58 61 72
6. Kundu S., Saha A., Sharma D., Pant C., Remote sensing and GIS based landslide susceptibility assessment using binary logistic regression model: a case study in the Ganeshganga Watershed, Himalayas. Journal of the Indian Society of Remote Sensing 2013 10.1007/s12524-012-0255-y
7. Pourghasemi H. R., Jirandeh A. G., Pradhan B., Xu C., Gokceoglu C., Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran. Journal of Earth System Science 2013 122 2 349 369 10.1007/s12040-013-0282-2
8. Pascale S., Parisi S., Mancini A., Landslide susceptibility mapping using artificial neural network in the urban area of Senise and San Costantino Albanese (Basilicata, Southern Italy). Computational Science and Its Applications-ICCSA 2013 2013 Springer 473 488 10.1007/978-3-642-39649-6-34
9. Wang H., Li J., Zhou B., Yuan Z., Chen Y., Application of a hybrid model of neural networks and genetic algorithms to evaluate landslide susceptibility. Natural Hazards and Earth System Sciences Discussions 2013 1 353 388
10. Venkatesan M., Thangavelu A., Prabhavathy P., An improved Bayesian classification data mining method for early warning landslide susceptibility model using GIS. Proceedings of the 7th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA '12) 2013 277 288
11. Bui D. T., Pradhan B., Lofman O., Revhaug I., Dick Ø. B., Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam. Natural Hazards 2013 66 2 707 730
12. Dong L., Li X., Peng K., Prediction of rockburst classification using Random Forest. Transactions of Nonferrous Metals Society of China 2013 23 472 477
13. Adoko A. C., Gokceoglu C., Wu L., Zuo Q. J., Knowledge-based and data-driven fuzzy modeling for rockburst prediction. International Journal of Rock Mechanics and Mining Sciences 2013 61 86 95
14. Dong L., Li X., Zhao G., Gong F., Fisher discriminant analysis model and its application to predicting destructive effect of masonry structure under blasting vibration of open-pit mine. Chinese Journal of Rock Mechanics and Engineering 2009 28 4 750 756 2-s2.0-65449134018
15. Dong L. J., Wang F. Y., Bai Y. F., Liu Y. F., A Fisher discriminant analysis model for prediction of seismic liquefaction of sand soil. Near-Surface Geophysics and Human Activity 2008 146 150
16. Dong L. J., Fu Y. H., Liu Y. F., Bai Y. F., A Fisher discriminant analysis model for classification of rocks surrounding in tunnel. 2 Proceedings of the Information Technology and Environmental System Sciences (Itess '08) 2008 632 636
17. Dong L. J., Hu D. T., Bai Y. F., Liu Y. F., Unascertained average grade model for surrounding rock classification on hydraulic tunnels. Progress in Safety Science and Technology 2008 7 2227 2231
18. Dong L.-J., Li X.-B., Bai Y.-F., A Fisher discriminant analysis model for classifying top coal cavability of the steep seam. Journal of the China Coal Society 2009 34 1 58 63 2-s2.0-61349101840
19. Dong L., Wang F., Comprehensive evaluation seismic stability of slopes based on unascermined measurcmem. The Chinese Journal of Geological Hazard and Control 2007 18 74 78
20. Dong L., Li X., An application of grey-general regression neural network for predicting landslide deformation of Dahu Mine in China. Advanced Science Letters 2012 6 577 581
21. Li X. B., Dong L. J., Zhao G. Y., Huang M., Liu A. H., Zeng L. F., Dong L., Chen G. H., Stability analysis and comprehensive treatment methods of landslides under complex mining environment-A case study of Dahu landslide from Linbao Henan in China. Safety Science 2012 50 4 695 704 2-s2.0-84856423655 10.1016/j.ssci.2011.08.049
22. Singh T. N., Kanchan R., Saigal K., Verma A. K., Prediction of p-wave velocity and anisotropic property of rock using artificial neural network technique. Journal of Scientific and Industrial Research 2004 63 1 32 38 2-s2.0-1642538202 (Pubitemid 38122924)
23. Vardhan H., Adhikari G. R., Govinda Raj M., Estimating rock properties using sound levels produced during drilling. International Journal of Rock Mechanics and Mining Sciences 2009 46 3 604 612 2-s2.0-60749116984 10.1016/j.ijrmms.2008.07.011
24. Huang R., Huang J., Ju N., Li Y., Automated tunnel rock classification using rock engineering systems. Engineering Geology 2013 156 20 27
25. Khabbazi A., Ghafoori M., Lashkaripour G., Cheshomi A., Estimation of the rock mass deformation modulus using a rock classification system. Geomechanics and Geoengineering 2013 8 46 52
26. Manoj K., Monjezi M., Prediction of flyrock in open pit blasting operation using machine learning method. International Journal of Mining Science and Technology 2013 23 3 313 316 10.1016/j.ijmst.2013.05.005
27. Dong L., Li X., Xu M., Li Q., Comparisons of random forest and support vector machine for predicting blasting vibration characteristic parameters. 26 Proceedings of the 1st International Symposium on Mine Safety Science and Engineering (ISMSSE '11) October 2011 1772 1781 2-s2.0-84856092862 10.1016/j.proeng.2011.11.2366
28. Salimi A., Esmaeili M., Utilising of linear and non-linear prediction tools for evaluation of penetration rate of tunnel boring machine in hard rock condition. International Journal of Mining and Mineral Engineering 2013 4 249 264
29. Verma A., Singh T., Comparative study of cognitive systems for ground vibration measurements. Neural Computing and Applications 2013 22 1, supplement 341 350
30. Verma A. K., Singh T. N., A neuro-fuzzy approach for prediction of longitudinal wave velocity. Neural Computing and Applications 2013 22 7-8 1685 1693 2-s2.0-84856808120 10.1007/s00521-012-0817-5
31. Xing J., Jiang A., Wen Z., Qin J., A nonlinear optimization technique of tunnel construction based on DE and LSSVM. Mathematical Problems in Engineering 2013 2013 11 10.1155/2013/980154 980154
32. Saeidi O., Torabi S. R., Ataei M., Prediction of the rock mass diggability index by using fuzzy clustering-based, ANN and multiple regression methods. Rock Mechanics and Rock Engineering 2013 10.1007/s00603-013-0426-3
33. Wang T., Cai L., Fu Y., Zhu T., A wavelet-based robust relevance vector machine based on sensor data scheduling control for modeling mine gas gushing forecasting on virtual environment. Mathematical Problems in Engineering 2013 2013 4 10.1155/2013/579693 579693
34. Tsai Y. L., Rainfall reliability evaluation for stability of municipal solid waste landfills on slope. Mathematical Problems in Engineering 2013 2013 10 653282 10.1155/2013/653282
35. Samui P., Kim D., Determination of reservoir induced earthquake using support vector machine and Gaussian process regression. Applied Geophysics 2013 10 229 234
36. Dong L., Li X., Ma C., Zhu W., Comparisons of logistic regression and Fisher discriminant classifier to seismic event identification. Disaster Advances 2013 6 8
37. Samui P., Multivariate adaptive regression spline (Mars) for prediction of elastic modulus of jointed rock mass. Geotechnical and Geological Engineering 2013 31 249 253
38. Breiman L., Random forests. Machine Learning 2001 45 1 5 32 2-s2.0-0035478854 10.1023/A:1010933404324 (Pubitemid 32933532)
39. Wang F., Dong L., Xu Z., Phreatic line predicted method-based SVM for stability analysis of tailing dam. Applied Mechanics and Materials 2011 44-47 3398 3402 2-s2.0-78651339981 10.4028/www.scientific.net/AMM.44-47.3398
40. Berchialla P., Foltran F., Gregori D., Naïve Bayes classifiers with feature selection to predict hospitalization and complications due to objects swallowing and ingestion among European children. Safety Science 2013 51 1 5
41. Fu Y.-H., Dong L.-J., Bayes discriminant analysis model and its application to the prediction and classification of rockburst. Journal of China University of Mining and Technology 2009 38 4 528 533 2-s2.0-68049112447
42. Domingos P., Pazzani M., On the optimality of the simple Bayesian classifier under zero-one loss. Machine Learning 1997 29 2-3 103 130 2-s2.0-0031269184 (Pubitemid 127510035)
43. Worth A. P., Cronin M. T. D., The use of discriminant analysis, logistic regression and classification tree analysis in the development of classification models for human health effects. Journal of Molecular Structure: THEOCHEM 2003 622 1-2 97 111 2-s2.0-0037424608 10.1016/S0166-1280(02)00622-X
44. Bai Y., Deng J., Dong L., Li X., Application of Fisher discriminant method in goaf collapse prediction. Mining Research and Development 2008 28 5 5
45. Bradley A. P., The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition 1997 30 7 1145 1159 2-s2.0-0031191630 (Pubitemid 127406521)